Tech-Trans Telecom (China) Ltd. accelerates time-to-market by 80% with Oracle

Tech-Trans cuts total cost of ownership by 40%, shortens sales cycle, and supports expansion with MySQL Enterprise Edition.

Tech-Trans Telecom (China) Ltd. (Tech-Trans) offers comprehensive and effective total solutions, including system integration and infrastructure design, to customers via partnerships with various global IT leaders, such as Oracle, IBM, and HPE. Its point-of-sale (POS) solution has approximately 50% market share in the Asia Pacific region’s retail industry, is included in the top 10 retail brands in Hong Kong, and has presence in 45% of large-scale shopping malls in China.

With rapid growth in online payment, customer relationship management (CRM), royalty, and membership modules, Tech-Trans wanted to ensure that the database for its online-to-offline (O2O) POS solution is scalable and enables its customers to expand globally. To meet this goal, the company moved to MySQL Enterprise Edition to improve the availability and scalability of system performance while reducing costs.

MySQL Enterprise Edition is a proven solution to ensure the reliability and scalability of our customers’ critical applications. We cut licensing cost by 40% and gained the ability to easily and rapidly expand our retail business across multiple countries without additional development.

Ricky LiuDirector, Tech-Trans Telecom (China) Ltd.

Business challenges

  • Deploy a high-performance and scalable open-source database and enable customers to accommodate surging transaction volume during sale periods, such as processing up to 140,000 daily transactions for a major department store in Hong Kong
  • Support growth by delivering a cost-effective O2O POS solution and helping small to large retailers easily expand their businesses to other regions

Why Tech-Trans Telecom (China) Ltd. Chose Oracle

“We were already using Oracle Database for over 10 years, so the migration to MySQL Enterprise Edition was easier and more cost effective than migrating to other databases. Oracle’s continuous development of the MySQL database and support services was also critical to our decision.”
—Ricky Liu, Director, Tech-Trans Telecom (China) Ltd.


  • Tech-Trans initially integrated MySQL Enterprise Edition with the mobile payment module of its O2O POS solution. After spending up to five months in development and testing, Tech-Trans successfully went live with the new platform. It plans to expand MySQL Enterprise Edition to the other core modules, including communications, CRM, and memberships.
  • “Our buying experience with Oracle was positive. The sales representative had great understanding of our business requirements and provided rapid response to our requests,” Liu said.
  • Slashed database investment by 40% by using the embedded database solution from MySQL Enterprise Edition to enable fast and easy deployment for small and large retailers across multiple countries at a lower cost
  • Improved time to market by 80% by seamlessly migrating Oracle Database to MySQL Enterprise Edition without requiring specialized skills or additional development
  • Saved significant time to provide database demonstration and shortened sales cycle by integrating MySQL Enterprise Edition—its mobile payment module delivered confidence and trust to customers that the POS solution is reliable and scalable due to Oracle’s market reputation 
  • Supported future expansion by developing the POS solution based on the commonly used MySQL database in China’s retail market and making it easier for customers to integrate with their multiple critical applications, including ERP, HR, and payroll  
  • Enabled retailers to provide better shopping experiences for their customers by leveraging the clustering feature of MySQL Enterprise Edition to ensure high availability for critical applications and rapidly processing massive volume of daily transactions, such as payment for cosmetics or apparel products, without downtime 
  • Simplified database management with MySQL Enterprise Edition by simply adding nodes to existing clusters as data load increases rather than upgrading the database
Published:November 27, 2018